Hiroki Naganuma

Answer

• Answer PDF

Reference

Bias-Variance

• Bias–variance tradeoff

The bias error is an error from erroneous assumptions in the learning algorithm. High bias can cause an algorithm to miss the relevant relations between features and target outputs (underfitting).

The variance is an error from sensitivity to small fluctuations in the training set. High variance may result from an algorithm modeling the random noise in the training data (overfitting).

CLE, MLE

• CNNの損失関数(Loss Function) その(1): 交差エントロピーとMSE

Unbiased Estimator

• Chapter 10 Supervised Learning
• 不偏推定量と一致推定量の意味